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Moving Shadow Detection using Deep Learning and Markov Random Field
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 Title & Authors
Moving Shadow Detection using Deep Learning and Markov Random Field
Lee, Jong Taek; Kang, Hyunwoo; Lim, Kil-Taek;
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 Abstract
We present a methodology to detect moving shadows in video sequences, which is considered as a challenging and critical problem in the most visual surveillance systems since 1980s. While most previous moving shadow detection methods used hand-crafted features such as chromaticity, physical properties, geometry, or combination thereof, our method can automatically learn features to classify whether image segments are shadow or foreground by using a deep learning architecture. Furthermore, applying Markov Random Field enables our system to refine our shadow detection results to improve its performance. Our algorithm is applied to five different challenging datasets of moving shadow detection, and its performance is comparable to that of state-of-the-art approaches.
 Keywords
Moving Shadow Detection;Convolutional Neural Network;Markov Random Field;Surveillance System;Object Detection;
 Language
Korean
 Cited by
1.
CNN 기반의 와일드 환경에 강인한 고속 얼굴 검출 방법,송주남;김형일;노용만;

한국멀티미디어학회논문지, 2016. vol.19. 8, pp.1310-1319 crossref(new window)
1.
Fast and Robust Face Detection based on CNN in Wild Environment, Journal of Korea Multimedia Society, 2016, 19, 8, 1310  crossref(new windwow)
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